Bayesian kernel projections for classification of high dimensional data.
Katarina DomijanSimon P. WilsonPublished in: Stat. Comput. (2011)
Keyphrases
- high dimensional data
- high dimensionality
- dimension reduction
- feature space
- dimensionality reduction
- high dimensional
- low dimensional
- input space
- data sets
- nearest neighbor
- subspace clustering
- support vector
- data points
- pattern recognition
- small sample size
- high dimensions
- regression problems
- high dimensional feature spaces
- feature extraction
- data analysis
- linear discriminant analysis
- dimensional data
- manifold learning
- similarity search
- low rank
- machine learning
- support vector machine
- multivariate temporal data
- decision trees
- feature selection
- clustering high dimensional data
- kernel methods
- class labels
- sparse representation
- training samples
- text classification
- learning algorithm
- high dimensional data sets
- feature vectors
- gaussian processes
- lower dimensional
- subspace learning
- high dimensional spaces
- image processing
- kernel matrix
- kernel machines
- training set
- kernel function
- knn
- multi dimensional
- image classification
- support vector machine svm